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◆ Analytical Chemistry2026-03-13· Chemistry

Rigid Restriction-Enabled Ultrabright Luminescence through Feather-like Metal-AIEgens Frameworks and Coupling the Collaborative Interfacial Recognition Mechanism for Pathogen Diagnosis

Zhaowen Cui, Chenjie Nie, Yuechun Li, Chenxin Ji, Yiyue Ma, Bingyan Li, Guo Hao, Jing Sun, Yanwei Ji, Jianlong Wang

原始摘要(英文原文)· Original abstract
The pursuit of high-performance immunochromatographic assays (ICAs) is hindered by inadequate signal brightness and the lack of understanding of the nanobiointerfacial recognition mechanism. Herein, a featherlike zinc-based metal-AIEgen framework (Zn-TCPE MAF) to concurrently address these dual challenges is constructed for ultrasensitive Salmonella typhimurium ICA detection. The rigid framework restricts intramolecular motion of the tetraphenylethylene (TCPE) ligand, yielding the fluorescent enhancement by 4.85-fold, ultrabright emitter with a 9.5-fold enhanced quantum yield (44.17%) and prolonging the fluorescent lifetimes from 1.65 to 7.42 ns. The ultrafast electron dynamics mechanism was revealed by femtosecond transient absorption spectroscopy, demonstrating the rigid restriction accelerates the internal conversion process to 247.62 fs, thereby effectively suppressing the nonradiative decay channel. Moreover, isothermal titration calorimetry quantitatively deciphers the interfacial recognition mechanism, revealing a spontaneous (Δ G <0), high-affinity ( K a = 1.72 × 10 7 M –1 ) antibody conjugation driven by synergistic electrostatic interaction, hydrogen bonding (Δ H <0), and hydrophobic interactions (Δ S >0). Leveraging these merits, the fabricated fluorescent ICA strip achieves a detection limit of 145 CFU mL –1, representing a >34-fold sensitivity improvement over conventional AuNP-based strips, with excellent specificity, stability, repeatability, and feasibility in various food samples, paving a synergistic avenue for next-generation ICA diagnostics.
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Rigid Restriction-Enabled Ultrabright Luminescence through Feather-like Metal-AIEgens Frameworks and Coupling the Collaborative Interfacial Recognition Mechanism for Pathogen Diagnosis — 科研速览 Science Skim